Sensitivity- and Gradient-Enhanced Hetero (ω1) Half-Filtered TOCSY Experiment for Measuring Long-Range Heteronuclear Coupling Constants

An enhanced version of the X(ω₁) half-filtered TOCSY experiment for measurement of long-range heteronuclear coupling constants is proposed which yields high-quality spectra with substantially increased sensitivity and resolution. The modified method features gradient-enhanced X filtering sequences, broadband homonuclear decoupling duringt₁, optional¹J_XHscaling in theF₁domain, and gradient coherence selection in combination with the sensitivity-enhanced protocol for the TOCSY transfer. These modifications extend the applicability of the method—coupling constants can be measured accurately for natural abundance samples at low concentrations and for compounds yielding complex spectra. Computer-aided analysis of E.COSY-type multiplets is applied for the determination of heteronuclear long-range coupling constants.     

Bootstrap bandwidth selection in kernel density estimation from a contaminated sample

In this paper we consider kernel estimation of a density when the data are contaminated by random noise. More specifically we deal with the problem of how to choose the bandwidth parameter in practice. A theoretical optimal bandwidth is defined as the minimizer of the mean integrated squared error. We propose a bootstrap procedure to estimate this optimal bandwidth, and show its consistency. These results remain valid for the case of no measurement error, and hence also summarize part of the theory of bootstrap bandwidth selection in ordinary kernel density estimation. The finite sample performance of the proposed bootstrap selection procedure is demonstrated with a simulation study. An application to a real data example illustrates the use of the method. This research was supported by ‘Projet d’Actions de Recherche Concertées’ (No. 98/03-217) from the Belgian government. Financial support from the IAP research network nr P5/24 of the Belgian State (Federal Office for Scientific, Technical and Cultural Affairs) is also gratefully acknowledged.     

Stochastic linear knapsack programming problem and its application to a portfolio selection problem

In this paper a probability maximization model of a stochastic linear knapsack problem is considered where the random variables consist of several groups with mutually correlated ones. We propose a solution algorithm to the equivalent nonlinear fractional programming problem with a simple ranking method. This approach will be effectively applied to one of the portfolio selection problems.     

基于免疫原理的蚁群系统及其应用

针对蚁群算法在寻优过程中容易出现停滞现象,同意在该算法中引入免疫机制,将待求解问题看成抗原,而问题的解看成抗体,通过基于浓度的选择机制和多样性保持策略来提高蚁群算法的全局搜索能力和避免停滞现象.对TSP问题的仿真实验结果表明,该算法极大地提高了搜索能力和避免了停滞现象.     

On polynomial selection for the general number field sieve

The general number field sieve (GNFS) is the asymptotically fastest algorithm for factoring large integers. Its runtime depends on a good choice of a polynomial pair. In this article we present an improvement of the polynomial selection method of Montgomery and Murphy which has been used in recent GNFS records.

     

Influence of energy transfer on the intensity pattern of vibronic excitation studied by reduced density-matrix theory

Intensity pattern of the vibronic transitions of a molecular dimer consisting of two molecules interacting through the Coulombic coupling is theoretically studied using a reduced density-matrix approach. The monomeric molecules are assumed to be electronic two-state systems. A single vibration mode with a high frequency and a continuous distribution of low-frequency phonons represented by the Ohmic spectral density are coupled to the electronic transition of the respective molecules. The spin-Boson model is employed to include the effect of electron-vibration and electron-phonon couplings. The intermolecular Coulombic coupling is assumed to be weak (inducing the Förster type of energy transfer process). It is found that, in addition to the well-known excitonic shifts, the intensity of the vibronic side bands reduces with the intermolecular coupling strength in the J-aggregate type of dimer while it increases in the H-aggregate type. When the vibronic bands are blurred by the broadening resulting from the coupling of the electrons to the continuous distribution of the phonons, the absorption line shape shows a wide range of variation depending on the strength of the intermolecular coupling.     

Influence of the pile shape on wind erosion CFD emission simulation

When designing an open storage system for bulk material like coal or iron ore, operational and investment parameters are to be considered. Those inputs are always managed by engineers and prolific literature can be found. But entering into environmental parameters like wind erosion, few methodologies are available, US EPA being one of the most extensive. This source is focused on certain conditions of wind direction, pile shape, etc. what sometimes are not matching the most interesting way of storing the material: area restrictions, stacking means, etc. Based on state of the art computational fluid dynamics (CFD) software, in this case we have used ANSYS CFX 5.7., modelling system was developed and compared to EPA results for conical and oval with flattop piles. After adjusting the calculation process and selecting the most effective variables, the semicircular shape was studied finding that for the same amount of material stored, lower emissions and wind erosions are to be expected; however depending on wind direction higher values of friction per surface unit are found but due to its higher volume of storage per square metre, the balance is positive to the semicircular pile.     

A Comparative Investigation on Model Selection in Independent Factor Analysis

With uncorrelated Gaussian factors extended to mutually independent factors beyond Gaussian, the conventional factor analysis is extended to what is recently called independent factor analysis. Typically, it is called binary factor analysis (BFA) when the factors are binary and called non-Gaussian factor analysis (NFA) when the factors are from real non-Gaussian distributions. A crucial issue in both BFA and NFA is the determination of the number of factors. In the literature of statistics, there are a number of model selection criteria that can be used for this purpose. Also, the Bayesian Ying-Yang (BYY) harmony learning provides a new principle for this purpose. This paper further investigates BYY harmony learning in comparison with existing typical criteria, including Akaik’s information criterion (AIC), the consistent Akaike’s information criterion (CAIC), the Bayesian inference criterion (BIC), and the cross-validation (CV) criterion on selection of the number of factors. This comparative study is made via experiments on the data sets with different sample sizes, data space dimensions, noise variances, and hidden factors numbers. Experiments have shown that for both BFA and NFA, in most cases BIC outperforms AIC, CAIC, and CV while the BYY criterion is either comparable with or better than BIC. In consideration of the fact that the selection by these criteria has to be implemented at the second stage based on a set of candidate models which have to be obtained at the first stage of parameter learning, while BYY harmony learning can provide not only a new class of criteria implemented in a similar way but also a new family of algorithms that perform parameter learning at the first stage with automated model selection, BYY harmony learning is more preferred since computing costs can be saved significantly.     

Reject inference,augmentation, and sample selection

Many researchers see the need for reject inference in credit scoring models to come from a sample selection problem whereby a missing variable results in omitted variable bias. Alternatively, practitioners often see the problem as one of missing data where the relationship in the new model is biased because the behaviour of the omitted cases differs from that of those who make up the sample for a new model. To attempt to correct for this, differential weights are applied to the new cases. The aim of this paper is to see if the use of both a Heckman style sample selection model and the use of sampling weights, together, will improve predictive performance compared with either technique used alone. This paper will use a sample of applicants in which virtually every applicant was accepted. This allows us to compare the actual performance of each model with the performance of models which are based only on accepted cases.     

Continuous Selections and Locally Pseudocompact Groups

We characterize locally pseudocompact groups by means of the selection theory. Our result is the selection version of the well-known Comfort—Ross theorem on pseudocompactness which states that a topological group is pseudocompact if and only its Stone—Čech compactification is a topological group.